electricsheepafrica/africa-kenya-new-sewerage-connection-in-the-country

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- water-sanitation-and-hygiene-wash
- ken
pretty_name: "Kenya - New sewerage Connections in the country"
dataset_info:
splits:
- name: train
num_examples: 48
- name: test
num_examples: 12
---

# Kenya - New sewerage Connections in the country

**Publisher:** Kenya Open Data Initiative (inactive) · **Source:** [HDX](https://data.humdata.org/dataset/kenya-new-sewerage-connection-in-the-country) · **License:** `cc-by` · **Updated:** 2024-09-13

---

## Abstract

Data on the new sewerage connections made.

Each row in this dataset represents time-series observations. Temporal coverage is indicated by the `date` column(s). Geographic scope: **KEN**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Water, sanitation and hygiene (wash) |
| **Unit of observation** | Time-series observations |
| **Rows (total)** | 60 |
| **Columns** | 13 (10 numeric, 2 categorical, 1 datetime) |
| **Train split** | 48 rows |
| **Test split** | 12 rows |
| **Geographic scope** | KEN |
| **Publisher** | Kenya Open Data Initiative (inactive) |
| **HDX last updated** | 2024-09-13 |

---

## Variables

**Geographic** — `factory` (range 0.0–4.0).

**Temporal** — `date`.

**Identifier / Metadata** — `objectid` (range 0.0–57.0), `esa_source` (HDX), `esa_processed` (2026-04-09).

**Other** — `commercial` (range 0.0–32.0), `domestic` (range 1.0–362.0), `school` (range 0.0–2.0), `government` (range 0.0–2.0), `kiosk` (range 0.0–2.0) and 3 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-kenya-new-sewerage-connection-in-the-country")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `date` | datetime64[ns] | 1.7% | |
| `commercial` | float64 | 3.3% | 0.0 – 32.0 (mean 11.7759) |
| `domestic` | float64 | 3.3% | 1.0 – 362.0 (mean 164.0862) |
| `school` | float64 | 3.3% | 0.0 – 2.0 (mean 0.1552) |
| `factory` | float64 | 3.3% | 0.0 – 4.0 (mean 0.1207) |
| `government` | float64 | 3.3% | 0.0 – 2.0 (mean 0.0517) |
| `kiosk` | float64 | 3.3% | 0.0 – 2.0 (mean 0.1207) |
| `water_projects` | float64 | 3.3% | 0.0 – 0.0 (mean 0.0) |
| `records_sewered` | float64 | 3.3% | 1.0 – 388.0 (mean 176.3103) |
| `no_sewer` | float64 | 3.3% | 1.0 – 318.0 (mean 133.7414) |
| `objectid` | float64 | 3.3% | 0.0 – 57.0 (mean 28.5) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-09 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `commercial` | 0.0 | 32.0 | 11.7759 | 10.0 |
| `domestic` | 1.0 | 362.0 | 164.0862 | 170.5 |
| `school` | 0.0 | 2.0 | 0.1552 | 0.0 |
| `factory` | 0.0 | 4.0 | 0.1207 | 0.0 |
| `government` | 0.0 | 2.0 | 0.0517 | 0.0 |
| `kiosk` | 0.0 | 2.0 | 0.1207 | 0.0 |
| `water_projects` | 0.0 | 0.0 | 0.0 | 0.0 |
| `records_sewered` | 1.0 | 388.0 | 176.3103 | 183.5 |
| `no_sewer` | 1.0 | 318.0 | 133.7414 | 139.5 |
| `objectid` | 0.0 | 57.0 | 28.5 | 28.5 |

---

## Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 13 exact duplicate rows were removed. 1 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

---

## Limitations

- Data originates from Kenya Open Data Initiative (inactive) and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/kenya-new-sewerage-connection-in-the-country) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_kenya_new_sewerage_connection_in_the_country,
title = {Kenya - New sewerage Connections in the country},
author = {Kenya Open Data Initiative (inactive)},
year = {2024},
url = {https://data.humdata.org/dataset/kenya-new-sewerage-connection-in-the-country},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*